High-content imaging, immunoblot and immunofluorescence data related to: Caprin-1 binding to the critical stress granule protein G3BP1 is influenced by pH

Schulte, Tim, Karolinska Institute, https://orcid.org/0000-0002-7322-8933

Han, Xiao, Karolinska Institute, https://orcid.org/0000-0003-0879-4119

Williams, Lucy, Karolinska Institute

Kedersha, Nancy, Harvard Medical School

Fleck, Jonas Simon, Karolinska Institute

Tan, Timothy J. C., Karolinska Institute

Dopico, Xaquin Castro, Karolinska Institute, https://orcid.org/0000-0002-9005-6774

Olsson, Anders, Royal Institute of Technology

Morro, Ainhoa Moliner, Karolinska Institute

Hanke, Leo, Karolinska Institute, https://orcid.org/0000-0001-5514-2418

Nilvebrant, Johan, Royal Institute of Technology

Giang, Kim Anh, Royal Institute of Technology

Nygren, Per-Åke, Royal Institute of Technology

Anderson, Paul, Harvard Medical School

Achour, Adnane, Karolinska Institute

McInerney, Gerald M., Karolinska Institute, https://orcid.org/0000-0003-2257-7241

Panas, Marc, Karolinska Institute

timpschu@gmail.com, marcdpanas@gmail.com

Published Sep 22, 2023 on Dryad. https://doi.org/10.5061/dryad.k98sf7mb8

Cite this dataset

Schulte, Tim et al. (2023). High-content imaging, immunoblot and immunofluorescence data related to: Caprin-1 binding to the critical stress granule protein G3BP1 is influenced by pH [Dataset]. Dryad. https://doi.org/10.5061/dryad.k98sf7mb8

Abstract

G3BP is the central node within stress-induced protein–RNA interaction networks known as stress granules (SGs). The SG-associated proteins Caprin-1 and USP10 bind mutually exclusively to the NTF2 domain of G3BP1, promoting and inhibiting SG formation, respectively. Herein, we present the crystal structure of G3BP1-NTF2 in complex with a Caprin-1-derived short linear motif (SLiM). Caprin-1 interacts with His-31 and His-62 within a third NTF2-binding site outside those covered by USP10, as confirmed using biochemical and biophysical-binding assays. Nano-differential scanning fluorimetry revealed reduced thermal stability of G3BP1-NTF2 at acidic pH. This destabilization was counterbalanced significantly better by bound USP10 than Caprin-1. The G3BP1/USP10 complex immunoprecipated from human U2OS cells was more resistant to acidic buffer washes than G3BP1/Caprin-1. Acidification of cellular condensates by approximately 0.5 units relative to the cytosol was detected by ratiometric fluorescence analysis of pHluorin2 fused to G3BP1. Cells expressing a Caprin-1/FGDF chimera with higher G3BP1-binding affinity had reduced Caprin-1 levels and slightly reduced condensate sizes. This unexpected finding may suggest that binding of the USP10-derived SLiM to NTF2 reduces the propensity of G3BP1 to enter condensates.

README: Supplementary data to rsob.220369: high-throughput imaging datasets and western blot images.

Overview of uploaded ZIP folders

In this repository following ZIP folders were deposited.
Listed with NAME of the ZIP-folder, SIZE, and a group-TAG. Analysis scripts related to the folders are available on GITHUB

NAME	SIZE	TAG	GITHUB
Images_Blots.zip	216.08 MB	@Images_1	-
pipelines_G3BP1.zip	430.17 KB	@CPpipelines_1	https://derpaule.github.io/RSOB-22-0369_condensates_GFP-G3BP1
img_plate2171.zip	2.77 GB	@HTimages_1	https://derpaule.github.io/RSOB-22-0369_condensates_GFP-G3BP1
img_plate2185.zip	3.47 GB	@HTimages_1	https://derpaule.github.io/RSOB-22-0369_condensates_GFP-G3BP1
img_plate21691.zip	3.27 GB	@HTimages_1	https://derpaule.github.io/RSOB-22-0369_condensates_GFP-G3BP1
img_plate1734.zip	1.09 GB	@HTimages_2	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-Caprin1
img_plate1735.zip	1.12 GB	@HTimages_2	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-Caprin1
img_plate1737.zip	1.16 GB	@HTimages_2	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-Caprin1
img_plate1740.zip	1.09 GB	@HTimages_2	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-Caprin1
pipelines_Caprin1.zip	473.67 KB	@CPpipelines_2	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-Caprin1
LLPS_GFP-G3BP1.zip	320.97 MB	@HTimages_3	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-G3BP1
LLPS_GFP-Caprin-1.zip	181.39 MB	@HTimages_4	https://github.com/derpaule/RSOB-22-0369_condensates_GFP-Caprin1

GENERAL NOTES

notes on tag groups:

@HTimages_1 group comprises high-throughput imaging datasets of cellular GFP-G3BP condensation assays presented in Figure 5 of the manuscript.
@HTimages_2 group comprises high-throughput imaging datasets of cellular GFP-Caprin condensation assays presented in Figure 7 of the manuscript.
@HTimages_3 group comprises high-throughput imaging datasets of in-vitro reconstituted GFP-G3BP condensation assays (LLPS), presented in Figure 5 of the manuscript.
@HTimages_4 group comprises high-throughput imaging datasets of in-vitro reconstituted GFP-Caprin condensation assays (LLPS), presented in Figure 7 of the manuscript.
@CPpipelines_1 group comprises Cellprofiler pipelines to analyse @HTimages_1
@CPpipelines_2 group comprises Cellprofiler pipelines to analyse @HTimages_2
@Images_1 group comprises raw image files used for presentation of Blots or IF data in main and supplemental figures

notes on deposited file formats:

.TIF or *.tif image files can be opened using standard software for images (ImageJ, Photoshop,...)
.xlsx can be opened using Microsoft Excel
.cpproj project files can be opened in Cellprofiler,
@CPpipelines_1 are associated with @HTimages_1,
@CPpipelines_2 are associated with @HTimages_2;
@HTimages_3 are analysed by 21-08-16_LLPScondensatecount_GFPimage.cpproj

structure of FILELIST

files are organised as follows:

ZIPfolder

folder
- filename
- filename description or placeholder (see below)

filename patterns in FILELIST

Filename pattern [A|B]_[1-10].tif would result in 20 tif image files:

A_1.tif ... A_10.tif
B_1.tif ... B_10.tif

* in filename patterns was used as regular expression:
*Mock*.tif would correspond to all TIF files containing the word "Mock"

The original image filenames were overly long and often comprised empty spaces or comma signs.
As requested by the curators, the filenames were shortened compared to the original filenames.
However, the uploaded cell profiler scripts or Excel sheets may refer to the old filenames.

To facilitate identification of the renamed files, we refer to the original filename as follows, using placeholders:
as i.e. 2Y = SG 40x ddG3- G1-wt- H31A- 2Y

If the shortened filenames comprised spaces or comma signs , these were substituted by x or X
and these changes are labeled as / /x/ and /,/X/ respectively

SPECIFIC NOTES TO TAG GROUPS

@HTimages_1 and @HTimages_2

comprise high-throughput (HT) imaging datasets that can be analysed by opening the associated pipelines @CPpipelines_1 and @CPpipelines_2 in Cellprofiler
TIF files can also be viewed using any image viewing software ImageJ.

specifics to filename pattern:

[A01|B01|C01] identifiers for cell-lines expressing different G3BP or Caprin-1 variants, specified in deposited pipelines @CPpipelines_1 and @CPpipelines_2
[s1-s100] recorded wells for each cell-line
w[1-2]/w3 each well was measured at three wavelengths

@HTimages_3 and @HTimages_4 datasets

comprise high-throughput (HT) imaging datasets that can be analysed by opening the associated pipeline "21-08-16_LLPScondensatecountGFPimage.cpproj" in Cellprofiler
TIF files can also be viewed using any image viewing software (https://imagej.nih.gov/ij/download.html).

specifics to filename pattern:

[2Y|H31A|wt] identifiers for cell-lines expressing different G3BP variants, as specified in manuscript
[wt|FGDF] identifier for Caprin-1 variant
[5|10|15|20|25|30] measured concentrations in micromolar
[1|2|3] number of replicate
ch0[0|1] recorded channel; channel 0 is the relevant channel for GFP

@Images_1

raw images used for the figures presented in the manuscript, organised in folder and subfolders according to Figures in manuscript.

FILELIST

@HTimages_1

img_plate2171.zip

plate_01: 1200 TIF image files
- 2Y_[A01|B01|B02|B03]_[s1-s100]_w[1-2].TIF
- 2Y_[A01|B01|B02|B03]_[s1-s100]_w3.tif
- with placeholder: 2Y = SG 40x ddG3- G1-wt- H31A- 2Y
plate_02: 1200 TIF image files with following naming pattern:
- 2Y_[C01|D01|D02|D03]_[s1-s100]_w[1-2].TIF
- 2Y_[C01|D01|D02|D03]_[s1-s100]_w3.tif
- with placeholder: 2Y = SG 40x ddG3- G1-wt- H31A- 2Y

img_plate2185.zip

plate_01: 1200 TIF image files with following
- 2Y_[A01|B01|B02|B03]_[s1-s100]_w[1-2].TIF
- 2Y_[A01|B01|B02|B03]_[s1-s100]_w3.tif
- with placeholder: 2Y = SG 40x ddG3- G1-wt- H31A- 2Y
plate_02: 1200 TIF image files with following
- 2Y_[C01|D01|D02|D03]_[s1-s100]_w[1-2].TIF
- 2Y_[C01|D01|D02|D03]_[s1-s100]_w3.tif
- with placeholder: 2Y = SG 40x ddG3- G1-wt- H31A- 2Y

img_plate21691.zip

plate_01: 1200 TIF image files with following
- 2Y_[A01|B01|B02|B03]_[s1-s100]_w[1-2].TIF
- 2Y_[A01|B01|B02|B03]_[s1-s100]_w3.tif
- with placeholder: 2Y = SG 40x ddG3- G1-wt- H31A- 2Y
plate_02: 1200 TIF image files with
- 2Y_[C01|D01|D02|D03]_[s1-s100]_w[1-2].tif
- 2Y_[C01|D01|D02|D03]_[s1-s100]_w3.TIF
- with placeholder: 2Y = SG 40x ddG3- G1-wt- H31A- 2Y

@HTimages_2

img_plate1734.zip

1734_A01: 300 TIF image files with following naming pattern:
- FGDF_A01_[s1-s100]_w[1-2].tif
- FGDF_A01_[s1-s100]_w3.TIF
1734_A02: 300 TIF image files with following naming pattern:
- FGDF_A02_[s1-s100]_w[1-2].tif
- FGDF_A02_[s1-s100]_w3.TIF
1734_B01: 300 TIF image files with following naming pattern:
- FGDF_B01_[s1-s100]_w[1-2].tif
- FGDF_B01_[s1-s100]_w3.TIF
1734_B02: 300 TIF image files with following naming pattern:
- FGDF_B02_[s1-s100]_w[1-2].tif
- FGDF_B02_[s1-s100]_w3.TIF
with placeholder: FGDF = SG 40x Cap1-wt FGDF

img_plate1735.zip

1735_A01: 300 TIF image files with following naming pattern:
- FGDF_A01_[s1-s100]_w[1-2].tif
- FGDF_A01_[s1-s100]_w3.TIF
1735_A02: 300 TIF image files with following naming pattern:
- FGDF_A02_[s1-s100]_w[1-2].tif
- FGDF_A02_[s1-s100]_w3.TIF
1735_B01: 300 TIF image files with following naming pattern:
- FGDF_B01_[s1-s100]_w[1-2].tif
- FGDF_B01_[s1-s100]_w3.TIF
1735_B02: 300 TIF image files with following naming pattern:
- FGDF_B02_[s1-s100]_w[1-2].tif
- FGDF_B02_[s1-s100]_w3.TIF
with placeholder: FGDF = SG 40x Cap1-wt FGDF

img_plate1737.zip

1737_A01: 300 TIF image files with following naming pattern:
- FGDF_A01_[s1-s100]_w[1-2].tif
- FGDF_A01_[s1-s100]_w3.TIF
1737_A02: 300 TIF image files with following naming pattern:
- FGDF_A02_[s1-s100]_w[1-2].tif
- FGDF_A02_[s1-s100]_w3.TIF
1737_B01: 300 TIF image files with following naming pattern:
- FGDF_B01_[s1-s100]_w[1-2].tif
- FGDF_B01_[s1-s100]_w3.TIF
1737_B02: 300 TIF image files with following naming pattern:
- FGDF_B02_[s1-s100]_w[1-2].tif
- FGDF_B02_[s1-s100]_w3.TIF
with placeholder: FGDF = SG 40x Cap1-wt FGDF

img_plate1740.zip

1740_A01: 300 TIF image files with following naming pattern:
- FGDF_A01_[s1-s100]_w[1-2].tif
- FGDF_A01_[s1-s100]_w3.TIF
1740_A02: 300 TIF image files with following naming pattern:
- FGDF_A02_[s1-s100]_w[1-2].tif
- FGDF_A02_[s1-s100]_w3.TIF
1740_B01: 300 TIF image files with following naming pattern:
- FGDF_B01_[s1-s100]_w[1-2].tif
- FGDF_B01_[s1-s100]_w3.TIF
1740_B02: 300 TIF image files with following naming pattern:
- FGDF_B02_[s1-s100]_w[1-2].tif
- FGDF_B02_[s1-s100]_w3.TIF
with placeholder: FGDF = SG 40x Cap1-wt FGDF

@CPpipelines_1

pipelines_G3BP1.zip

6 Cellprofiler pipelines to analyse @Images_1
- SG_pipeline04_caprin_plate2169_01_GFPint02.cpproj
- SG_pipeline04_caprin_plate2169_02_GFPint02.cpproj
- SG_pipeline04_caprin_plate2171_01_GFPint02.cpproj
- SG_pipeline04_caprin_plate2171_02_GFPint02.cpproj
- SG_pipeline04_caprin_plate2185_01_GFPint02.cpproj
- SG_pipeline04_caprin_plate2185_02_GFPint02.cpproj

@CPpipelines_2

pipelines_Caprin1.zip

5 Cellprofiler pipelines to analyse @Images_2
- SG_pipeline_chimera_1734_robust.cpproj
- SG_pipeline_chimera_1735_robust.cpproj
- SG_pipeline_chimera_1737_robust.cpproj
- SG_pipeline_chimera_1740_robust_CytoNorm.cpproj
- SG_pipeline_chimera_1740_robust.cpproj

@HTimages_3

LLPS_GFP-G3BP1.zip

21-08-16_LLPScondensatecount_GFPimage.cpproj Cellprofiler pipeline to analyse the images of @HTimages_3
21-11-02_LLPS_2Y
- LLPS_2Y_[2Y|H31A|wt]XxrG1-[2Y|H31A|wt]Xx[5|10|15|20|25|30]xuM-[1|2|3]_z0_ch0[0|1].tif
  - 108 TIF images of G3BP-[WT|2Y|H31A] spiked in at six concentrations\, measured in triplicate\, in two channels
  - with placeholders: LLPS_2Y_ = 21-11-02, LLPS, GFP-G1wt, H31A, 2Y, rG1-wt, H31A, 2Y, 30-5 uM, 1h_GFP-G1- + / /x/ + /,/X/
- 21-11-02_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-11-03_LLPS_2Y
- LLPS_2Y_[2Y|H31A|wt]XxrG1-[2Y|H31A|wt]Xx[0|5|10|15|20|25|30]xuM-[1|2|3]_z0_ch0[0|1].tif
  - 126 TIF images of G3BP-[WT|2Y|H31A] spiked in at six concentrations\, measured in triplicate\, in two channels
  - with placeholder: LLPS_2Y_ = 21-11-03, LLPS, GFP-G1wt, H31A, 2Y, rG1-wt, H31A, 2Y, 30-5 uM, 1h_GFP-G1- + / /x/ + /,/X/
- 21-11-04_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-12-03_LLPS_2Y
- LLPS_2Y_[2Y|H31A|wt]XxrG1-[2Y|H31A|wt]Xx[0|5|10|15|20|25|30]xuMXx1h-[1|2|3]_z0_ch0[0|1].tif
  - 126 TIF images of G3BP-[WT|2Y|H31A] spiked in at six concentrations\, measured in triplicate\, in two channels
  - with placeholder: LLPS_2Y_ = 21-12-03, LLPS, GFP-G1wt, H31A, 2Y, rG1-wt, H31A, 2Y, 30-0 uM, 1h_GFP-G1- + / /x/ + /,/X/
- 21-12-03_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-12-10_LLPS_2Y
- LLPS_2Y_[2Y|H31A|wt]XxrG1-[2Y|H31A|wt]Xx[0|5|10|15|20|25|30]xuM-[1|2|3]_z0_ch0[0|1].tif
  - 126 TIF images of G3BP-[WT|2Y|H31A] spiked in at six concentrations\, measured in triplicate\, in two channels
  - with placeholder: LLPS_2Y_ = 21-12-10, LLPS, GFP-G1wt, H31A, 2Y, rG1-wt, H31A, 2Y, 30-0 uM_GFP-G1- + / /x/ + /,/X/
- 21-12-10_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet

@HTimages_4

LLPS_GFP-Caprin-1.zip

21-08-17_LLPS_FGDF
- LLPS_FGDF_[wt|FGDF]XxrG1-wtx[1.25|2.5|5|10|20]xuMXx1h-[1|2|3]_z0_ch0[0|1].tif
  - 60 TIF images of GFP-Cap1-[wt|FGDF] spiked in at 5 concentrations in triplicate measured in two channels
  - with placeholders: LLPS_FGDF_ = 21-08-17, LLPS, GFP-Cap1-wt vs FGDF 5 mg-mL, rG1-wt_LLPS, GFP-Cap1- + / /x/ + /,/X/
- 21-08-17_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-08-23_LLPS_FGDF
- LLPS_FGDF_[wt|FGDF]XxrG1-wtx[1.25|2.5|5|10|20]xuMXx1h-[1|2|3]_z0_ch0[0|1].tif
  - 60 TIF images of GFP-Cap1-[wt|FGDF] spiked in at 5 concentrations in triplicate measured in two channels
  - with placeholders: LLPS_FGDF_ = 21-08-23, LLPS, GFP-Cap1-wt vs FGDF, 5 mg-ml, rG1-wt_LLPS, GFP-Cap1- + / /x/ + /,/X/
- 21-08-23_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-08-27_LLPS_FGDF
- LLPS_FGDF_[wt|FGDF]XxrG1-wtx[1.25|2.5|5|10|20]xuMXx1h-[1|2|3]_z0_ch0[0|1].tif
  - 60 TIF images of GFP-Cap1-[wt|FGDF] spiked in at 5 concentrations in triplicate measured in two channels
  - with placeholders: LLPS_FGDF_ = 21-08-27, LLPS, GFP-Cap1-wt vsFGDF, 5 mg-mL, rG1-wt 1h_LLPS, GFP-Cap1- + / /x/ + /,/X/
- 21-08-27_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-12-13_LLPS_FGDF
- LLPS_FGDF_[wt|FGDF]XxrG1-wtXx[0|5|10|15|20|25|30]xuM-[1|2|3]_z0_ch0[0|1].tif
  - 84 TIF images of GFP-Cap1-[wt|FGDF] spiked in at 7 concentrations in triplicate measured in two channels
  - with placeholders: LLPS_FGDF_ = 21-12-13, LLPS, GFP-Cap1-wt vs FGDF, 4.2 mg, rG1-wt 30-0 uM_GFP-Caprin1-+ / /x/ + /,/X/
- 21-12-13_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet
21-12-23_LLPS_FGDF
- LLPS_FGDF_[wt|FGDF]XxrG1x[0|5|10|15|20|25|30]xuM-2_z0_ch0[0|1].tif
  - 84 TIF images of GFP-Cap1-[wt|FGDF] spiked in at 7 concentrations in triplicate measured in two channels
  - with placeholder + substitutions: LLPS_FGDF_ = 21-12-23, LLPS, GFP-Cap wt vs FGDF, rG1 0-30 uM, 1h_GFP-Cap1- + / /x/ + /,/X/
- 21-12-23_Analysis_Coverage.xlsx Analysis of Cellprofiler output in Excel sheet

@Images_1

Images_Blots.zip

MainFigures
- Figure2
  - Figure2A_westernblots
    - 2s_IPs360-370_Cap1_Actin_G1_G2.tif
    - 10s_Cap1_GAPDH_G1rerunlysates.tif
    - 10s_Cap1_GAPDH_G1_lysates.tif
    - 10s_IPs371-381_Cap1_G1_G2.tif
    - 30s_Cap1_GAPDH_G1_lysates.tif
    - 180s_IPs360-370_Cap1_Actin_G1_G2.tif
    - 300s_IPs371-381_Cap1_G1_G2.tif
    - 500s_IPs371-381_Cap1_G1_G2.tif
    - white_Cap1_GAPDH_G1rerunlysates.tif
    - white_Cap1_GAPDH_G1_lysates.tif
    - white_IPs360-370_Cap1_Actin_G1_G2.tif
    - white_IPs371-381_Cap1_G1_G2.tif
- Figure4
  - Figure4B_westernblots
    - WB_1s_G1_Cap1_USp10_GAPDH.tif
    - WB_5s_UBAP2L_USP10_Cap1_G1_GAPDH_RPS6.tif
    - WB_10s_G1_Cap1_USp10_GAPDH.tif
    - WB_20s_UBAP2L_USP10_Cap1_G1_GAPDH_RPS6.tif
    - WB_60s_UBAP2L_USP10_Cap1_G1_GAPDH_RPS6.tif
    - WB_480s_UBAP2L_USP10_Cap1_G1_GAPDH_RPS6.tif
    - WB_white_G1_Cap1_USp10_GAPDH.tif
    - WB_white_UBAP2L_USP10_Cap1_G1_GAPDH_RPS6.tif
- Figure5
  - Figure5A_IFimages
    - 2Y_A01_s56_w[1|2|3].tif 3 TIF images
    - 2Y_B01_s100_w[1|2|3].tif 3 TIF images
    - 2Y_B02_s20_w[1|2|3].tif 3 TIF images
    - 2Y_B03_s53_w1[1|2|3].tif 3 TIF images
  - **Figure5D_IFimages
    - LLPS_2Y_[2Y|H31A|wt]XxrG1-[2Y|H31A|wt]Xx[0|5|10|15|20|25|30]xuM-1_z0_ch0[0|1].tif 42 TIF images of G3BP-[WT|2Y|H31A] spiked in at six concentrations\, two channels
- Figure6
  - Figure6A_IFimages
    - ddG32_z0_ch00.tif
    - ddG32_z0_ch01.tif
  - **Figure6D_IFimages
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c1_green.tif
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c1-3.tif
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c1-c3.tif
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c1.tif
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c2.tif
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c3_blue.tif
    - 22-01-112nd_Phlu2-G1rG1pH7_4-4-ImageExport-10_c3.tif
- Figure7
  - Figure7A_westernblot
    - WB_10s_G1_GAP_FMR_Cap1.tif
    - wb_500s_O.N.FMR1.tif
    - WB_white_G1_GAP_FMR_Cap1.tif
    - wb_white_O.N.FMR1.tif
  - Figure7C_IFimages
    - FGDF_A01_s10_w[1|2|3].tif 3 TIF images
    - FGDF_A02_s9_w[1|2|3].tif 3 TIF images
    - FGDF_B02_s9_w[1|2|3].tif 3 TIF images
  - Figure7F_IFimages
    - LLPS_FGDF_[wt|FGDF]XxrG1-wtXx[0|5|10|15|20|25|30]xuM-1_z0_ch0[0|1].tif 28 TIF images of GFP-Cap1-[wt|FGDF] spiked in at 7 concentrations in triplicate measured in two channels
** SupplementalFigures **
- SupplementalFigureS3
  - SupplementalFigureS3B_westernblot
    - 15-05-12_PoncU2OSCaprin1KO.tif
    - 240s_UBAP2L_G1_Cap1_GAPDH.tif
    - white_UBAP2L_G1_Cap1_GAPDH.tif
  - SupplementalFigureS3D_IFimages
    - U2OS-wt+U2OS-Cap1-KOg2_MockCap1-2.tif
    - U2OS-wt+U2OS-Cap1-KOg2_MockG3BP1.tif
    - U2OS-wt+U2OS-Cap1-KOg2_MockTIA1.tif
    - U2OS-wt+U2OS-Cap1-KOg2_SACap1-2.tif
    - U2OS-wt+U2OS-Cap1-KOg2_SAG3BP1.tif
    - U2OS-wt+U2OS-Cap1-KOg2_SATIA1.tif
- SupplementalFigureS6
  - 10s_IPs_UBAP2L_G1_Cap1_USP10_GAPDH.tif
  - 10s_Lys_G3BP1reblot(good).tif
  - 30s_IPs_UBAP2L_G1_Cap1_USP10_GAPDH.tif
  - 240s_Lys_UBAP2L_G1_Cap1_GAPDH.tif
  - white_IPs_UBAP2L_G1_Cap1_USP10_GAPDH.tif
  - white_Lys_UBAP2L_G1_Cap1_GAPDH.tif
- SupplementalFigureS8
  - H31A_C02_s10_w1-merge-rgb.tif
  - H31A_C02_s10_w[1|2|3]-rgb.tif 3 TIFs
  - ddG_G1-wt-H31A-2Y_B01_s10_w3merge-rgb.tif
  - ddG_G1-wt-H31A-2Y_B01_s10_w[1|2|3]-rgb.tif 3 TIFs
- SupplementalFigureS9
  - LLPS_FGDF_[2y|H31A|wt]XxrG1-[2Y|H31A|wt]Xx20xuMXx[6.8|7.0|7.2|7.4|7.6|7.8]-1_z0_ch0[0|1].tif 36 TIF images

Methods

The deposited ZIP folders are described in following groups:

@HTimages_1
- high-throughput imaging datasets of cellular GFP-G3BP condensation assays presented in Figure 5 of the manuscript
- ZIP folders: img_plate2171.zip / img_plate2185.zip / img_plate21691.zip
@HTimages_2
- high-throughput imaging datasets of cellular GFP-Caprin condensation assays presented in Figure 7 of the manuscript.
- ZIP folders: img_plate1734.zip / img_plate1735.zip / img_plate1737.zip / img_plate1740.zip
@HTimages_3
- high-throughput imaging datasets of in-vitro reconstituted GFP-G3BP condensation assays (LLPS), presented in Figure 5 of the manuscript.
- ZIP folders: LLPS_GFP-G3BP1.zip
@HTimages_4
- high-throughput imaging datasets of in-vitro reconstituted GFP-Caprin condensation assays (LLPS), presented in Figure 7 of the manuscript.
- ZIP folders: LLPS_GFP-Caprin-1.zip
@CPpipelines_1
- Cellprofiler pipelines to analyse @HTimages_1
- ZIP folders: pipelines_G3BP1.zip t
@CPpipelines_2
- Cellprofiler pipelines to analyse @HTimages_2
- ZIP folders:pipelines_Caprin1.zip
@Images_1
- raw image files used for presentation of Blots or IF data in main and supplemental figures
- ZIP folders: Images_Blots.zip

The collection of datasets is described in the methods section of the associated manuscript (ms, https://royalsocietypublishing.org/doi/10.1098/rsob.220369)

@HTimages_1/@HTimages_2:
- ms section: 4.9.1. High-content microscopy:
- "Images were recorded with a Molecular Devices ImageXpress Micro microscope, equipped with a 20x or 40x objective, and illuminated with a mercury lamp and standard filters for DAPI, FITC, Cy3 and Cy5. Images were captured using a four-megapixel sCMOS digital camera with the manufacturer’s software MetaXpress, and raw TIF files were analyzed using CellProfiler (CP), ImageJ and Rstudio."
@HTimages_3/@HTimages_4
- ms section: 4.9.4. In vitro reconstituted condensate assays
- "Images were taken with a Supercontinuum Confocal Leica TCS SP5 X, equipped with a pulsed white light laser and a Leica HCX PL Apo 63x/1.40 oil objective. "
@Images_1
- ms section 4.8. Immunoprecipitation and immunoblotting
- ms section: 4.9. Immunofluorescence analysis

Usage notes

See README file for full details.

general notes on deposited file formats:
*.TIF or *.tif image files can be opened using standard software for images (ImageJ, Photoshop,...)
*.xlsx can be opened using Microsoft Excel
*.cpproj project files can be opened in Cellprofiler (https://cellprofiler.org/)

High-throughput (HT) imaging datasets can be analysed by opening the deposited Cellprofiler pipelines in Cellprofiler (https://cellprofiler.org/).
TIF files can also be viewed using any image viewing software (https://imagej.nih.gov/ij/download.html).

Scripts to analyse the Cellprofiler output, and additional information is found on Github:

https://github.com/derpaule/RSOB-22-0369

Funding

Swedish Research Council, Award: 2018-03843

Swedish Research Council, Award: 2018-03914

Swedish Cancer Society, Award: CAN 2018/829

Swedish Cancer Society, Award: CF 2018/603

Swedish Research Council, Award: 2018-02874

Swedish Society for Medical Research, Award: P16-0083

Stiftelsen Clas Groschinskys Minnesfond, Award: M2002

Swedish Cancer Society, Award: 2018/603

Swedish Cancer Society, Award: 2018/829

National Institutes of Health, Award: GM126901